Question 1

How does an AI project with Bowles Creative actually work?

Accepted Answer

It starts with a conversation — you describe the problem, we ask questions, and we figure out together what's worth building. From there we scope the work, agree on a fixed price, and get started. You work directly with Stephen and his team throughout. We build, you review, we iterate. No lengthy discovery phases, no disappearing for months.

Question 2

How much does a custom AI project cost?

Accepted Answer

It depends on what you need. For an initial AI strategy engagement — understanding where AI fits in your business and what's worth building — plan on $3,000–$4,000. For a custom AI application build, workflow automation, integration, or full deployment, budget $15,000 and up depending on scope. Every project is quoted at a fixed price with no hourly billing.

Question 3

What does AI actually look like inside a business?

Accepted Answer

It depends on the business. A financial advisory firm might use AI to ingest client data, flag irregularities, and surface reconciliation gaps — turning a day of analyst work into twenty minutes. A law firm might use it for contract intake triage, reading incoming documents and surfacing key clauses so attorneys spend time on judgment, not extraction. A SaaS company might use it to mine years of support tickets and product feedback for patterns — what's breaking, what customers want, what to build next. The throughline is the same: find where your team is doing repetitive, high-cognitive-load work on information that already exists in your systems, and build AI that handles that layer.

Question 4

How long does a project typically take?

Accepted Answer

It depends on what you're building. A strategy engagement usually wraps in two to three weeks. Most automation and integration projects run four to eight weeks. Custom AI application builds depend on scope, but six to twelve weeks is a typical range. We work in short cycles — you see progress early and often, not at the end of a long runway.

Question 5

Is my data secure? Where does it go?

Accepted Answer

For automation workflows, data moves through the platforms we use (Make, n8n, etc.) but is never stored by Bowles Creative — it stays within your systems and the integrations you authorize. For custom builds, data lives in infrastructure you control. When AI models are involved (OpenAI, Anthropic), we use their API — not consumer products — which means your data is not used for model training. For regulated industries or sensitive data, we discuss data handling explicitly as part of scoping.

Question 6

How do I know if AI is actually right for my business?

Accepted Answer

Honestly, it isn't always. AI works best when there's repetitive, high-volume work that already runs through your existing systems — information that needs to be extracted, routed, summarized, or acted on at a volume that makes doing it manually feel like a tax on your team's time. It's a poor fit when the core work requires relationship judgment, creative discretion, or when the underlying data simply doesn't exist yet. If you're not sure, the strategy engagement exists for exactly that — to figure out where it creates real value before committing to a build.

Question 7

Do you offer ongoing support after the project launches?

Accepted Answer

AI systems need attention after launch — models change, outputs drift, and the business problems you're solving evolve. Most clients move into an ongoing service retainer that covers monitoring what we built, tuning it as needed, and adding to it as new needs come up. Retainers average $1,000/month.

What an AI readiness assessment should actually look like.

Start with workflows, not tools.

Then inspect the data and systems.

Risk should shape the design.

A readiness assessment should end with a build path.

Readiness is a way to avoid expensive guessing.